SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks
|
|
- Emily Griffith
- 8 years ago
- Views:
Transcription
1 : Online Security Management and Reliability Toolkit for Water Distribution Networks Thomas Bernard, Mathias Braun Fraunhofer Institute IOSB Jochen Deuerlein 3S Consult GmbH Marie Maurel Veolia Environnement Olivier Piller, Denis Gilbert IRSTEA Andreas Korth, Reik Nitsche DVGW-Technologiezentrum Wasser Anne-Claire Sandraz Veolia Eau d Ile de France anne-claire.sandraz@veoliaeau.fr Fereshte Sedehizade Jean-Marc Weber Berliner Wasserbetriebe Communauté Urbaine de Strasbourg fereshte.sedehizade@bwb.de jean-marc.weber@strasbourg.eu Caty Werey Engees caty.werey@engees.unistra.fr ABSTRACT Water distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental contamination. Until now, no monitoring system is capable of protecting a WDN in real time. In the immediate future water service utilities that are installing water quantity and quality sensors in their networks will be producing a continuous and huge data stream for treating. The main objective of the project is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity and online simulation. Its field of application ranges from detection of deliberate contamination, including source identification and decision support for effective countermeasures, to improved operation and control of a WDN under normal and abnormal conditions. Keywords Water supply networks, contamination, online simulation, transport model INTRODUCTION Water Distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental contamination. In particular, the drinking water supply is at potential risk of being a terrorist target and contamination need to be detected in due time. The resource, the treatment plant or the distribution network may be contaminated with a deliberate injection of chemical, biological or radioactive contaminants. Several papers report deliberate contamination of a water distribution networks in the past as summarized in (Gleik, 2006). Until now, no monitoring system is capable to protect a WDN in real time. Powerful online sensor systems are currently developed and the prototypes are able to detect a small change in water quality. In the immediate future, water service utilities will install their networks with water quantity and water quality sensors. For taking appropriate decisions and countermeasures, WDN operators will need to dispose of: 1) a fast and reliable detection of abnormal events in the WDNs; 2) reliable online models both for the hydraulics and water quality predictions; 3) methods for contaminant source identification backtracking from the data history. Actually, in general none of these issues (1) (3) are available at the water suppliers. Consequently, the main 171
2 objective of the project is the development of an online security management toolkit for water distribution networks (WDN) that is based on sensor measurements of water quality as well as water quantity. Its main innovations are the detection of abnormal events with a binary classifier of high accuracy and the generation of real-time, reliable (i) flow and pressure values, (ii) water quality parameter values of the whole water network. Detailed information regarding contamination sources (localization and intensity) will be explored by means of the online running model, which is automatically calibrated to the measured sensor data. Its field of application ranges from detection of deliberate contamination including source identification and decision support for effective countermeasures to improve operation and control of a WDN under normal and abnormal conditions (dual benefit). Figure 1: In case of a toxic contamination of the water distribution network, the water suppliers will be supported by the security management toolkit. In this project, the technical research work is completed with a sociological, economical and management analysis. combines applied mathematics, civil and environment engineering, fluid mechanics research and social science and economics in a multidisciplinary approach. The French-German cooperative research project consists of end users (BWB in Germany, CU Strasbourg and Veolia Eau d Ile de France), technical and socio-economic research institutions (Fraunhofer IOSB, TZW, Irstea, ENGEES) and industrial partners on both French and German sides (Veolia, 3S Consult). System Concept and Objectives of The overall objective of the project is the development of an online security management toolkit for WDNs. The general system concept is sketched in Figure 2. The software solution relies on data treatment and assimilation from a sensor network of water quantity values (pressure, flow rate) and water quality values (e.g. chlorine residue, ph, conductivity, turbidity, temperature,). The core of the online security management toolkit consists of a grid of smart sensors in combination with an online simulation model. The boundary conditions of the network model are regularly updated by measurement data guaranteeing the compliance of the model with the observations. The consistency of the measurements is checked e.g. by use of an Artificial Neural Network. With this information the online security management toolkit is able to reflect the current hydraulic state of the entire system. In addition, monitoring of water quality parameters supports the detection of biochemical contamination of the drinking water. Figure 2: General system concept of The modules can be summarized as follows: 1. Event Detection and Alarm Generation: To enable a robust detection of changes in the water quality, a sensor data fusion module will evaluate the data of smart sensors. Online simulation model is used for plausibility check of the event detection. 2. Optimal sensor placement. A concept for the optimal placement of a defined number of quality sensors in a real-world network topology and an existing network of usual sensors (hydraulic state, physical/chemical parameters) will be developed and implemented as a software tool. It enables the user (e.g. WDN operators) to find optimal locations for early warning detection system (Propato and Piller, 2006; Deuerlein et al., 2010) and for parameter estimation (Piller, 1995; Fabrie et al., 2010). 172
3 3. Online Simulation: Generation of real-time, reliable (i) flow and pressure values, (ii) water quality parameter values of the whole water network 4. Transport model: A detailed experimental and simulation based study of the transport of conservative substances in real-world water drinking networks will be performed. A special focus is on the flow and distribution of substances at crosses and T-junctions as in most of the actual available WDN simulation software tools (e.g. EPANET) a complete mixing of the substances is assumed. These phenomena will be investigated by means of detailed 3D computational fluid dynamics (CFD) models. Later on, a simplified 1D model will be implemented due to the need of a short simulation time in the real-time management toolkit software. 5. Online contaminant source identification and mitigation of risks: A backtracking algorithm that uses the data history of the measurements has to be implemented. The merit of off-line methods (e.g.: Propato et al. 2007) and pseudo real-time ones (Preis and Ostfeld, 2011) will be studied compared to the developed online solution method. As a result of water quality sensor alarms, the possible localisations of the intrusion of contaminant can be calculated. 6. Risk analysis and impact assessment: Risk analysis and impact evaluation (real impacts and perceived ones) will be performed for the three aspects of sustainability: environmental, social and economical, combined with technical innovation. will improve the observability of water quality and quantity in the distribution network in near real-time. It acts as an early warning system as well as decision-support system in case of contamination events. Furthermore, it supports a better understanding of the physical and bio-chemical processes in the pipe systems. E.g., it will be possible to use it offline for training of staff by use of simulation. In the sequel we will focus on the concept and first results of online simulation and transport modelling. ONLINE SIMULATION The main difference between online and offline hydraulic simulation is that the boundary conditions (tank water levels, zone inflow, demands, etc.) and operational states of devices (like valve status, pump operations, etc.) of the online model are not predefined by the user, as it is true for the offline case, but derived from (near) real time data originating from the SCADA (Supervisory Control And Data Acquisition) system of the utility. Therefore these data of the online model are always up to date. The simulation based on online data is able to reflect the actual current state of the system much better than the offline model where the proper choice of the boundary conditions is based on historical data or the experience and the knowledge of the modeller. However, in practice, not all of the model parameters can be measured and transferred online due to financial and technical limitations. This applies in particular to the time varying demands of the customers. As a result, one major issue of online simulation is the proper estimation of the noisy data user demands. Therefore an online calibration tool will be developed that calculates (or estimates) the distribution of actual demands within the particular zones by minimizing a least-squares function of calculated and measured values of all available measurements of the zone such as in Piller et al. (2010). Another challenge of online simulation consists in the strong requirements for calculation time and data transfer. The objective is to run the online simulation cycle at least every five minutes including online calibration, data transfer and monitoring. In order to enhance the overall process a method for simplification of large water distribution system networks has been developed, which is based on topological decomposition of the network graph (Deuerlein et al. 2010; Deuerlein, 2008). On the one hand the method shall be used for the enhancement of the solution of the hydraulic calculations by a new method for reordering of the system of equations that has been published recently (Deuerlein and Simpson, 2012). On the other hand, graph decomposition can be used as general tool for adaptive modelling in the context of. In the context of the online simulation framework is not used only for the monitoring of the current state of the system but also for the management of mitigation measures in case of an accident. For that purpose the additional simulation modes look-ahead, what-if and reconstruction are required. Look-ahead simulations can be used for predicting the spread of contamination if the location of the source is known. What- If simulations support the fast and efficient development of counter measures like isolation of contaminant and flushing. Reconstruction of system states of the recent past is needed for the solution of the source identification problem in cases where alarms for contamination are released by the sensors but the source of contamination and its location are unknown. TRANSPORT MODEL Existing transport model tools are not adapted for online modelling and ignore some important phenomena that may be dominant when looking at the network in greater detail with an observation time of several minutes. 173
4 These phenomena are addressed in. In summary, it is important to consider: 1) Inertia terms to make slow transient predictions of the hydraulic state; 2) The hydrodynamic dispersion and possibly the molecular diffusion to improve the transport along a pipe and at junctions; 3) The imperfect mixing at T- and Cross junctions depending on velocity inlets; 4) The diameter reduction and the wall roughness (Shen, 2008). In a first project phase, these phenomena are investigated by means of 2D and 3D Finite Element simulations as well as in experimental studies (see next section). In the sequel, some first results of transport modelling are presented. Investigation of turbulent flow at T-junctions: When simulating the behaviour of pollutant at the junctions of pipes it is important to consider the effects of turbulence induced. For this, two turbulence models have been compared : 1) a large eddy simulation (LES) model that is more accurate but with large computational burden; and 2) a Reynolds-Averaged Navier- Stokes (RANS) model that neglects the small perturbations that are significant in the pollutant streamlines in the tubes. Figure 3 shows the differences between the two methods (RANS k-ε and LES Smagorinski Lilly). The inlet is West side and the two outlets are North and East. Figure 3: Comparison of turbulence simulation (velocity) using methods RANS (left) and LES (right) Simulating mass flow distribution at T-junctions: To adapt for 1D model more accurate than those used actually, we simulated many various configurations of T-junctions. The first results are used to define the methodology, to measure the conception and calculation time for one test case. The configuration is with one inlet and two outlets. Figure 4 shows the difference in distribution of the pollutant function of the shared flows of the two outlets. Main is the straight direction, secondary the one that turns 90 degrees. This demonstrates that it is important to simulate imperfect mixing for T-junction configuration. a) Main 20%, secondary 80% b) Main 50%, secondary 50% c) Main 80%, secondary 20% Figure 4: Influence of Mass Flow distribution with three case studies. Green represents the inlet; blue the main outlet and red the secondary outlet. Parameters: v=0.8m/s at the inlet, injection of 306g by constant mass flow. Influence of curvature T-junctions: In a first study the influence of the curvature at the joint of a T-junction on the flow are analysed. The diameter of the pipes is D=0.1m and velocity at the inlet is set to v=0.02 m/s, so the problem is laminar. Compared are a junction without curvature (Figure 5, left) to a curved junction with the radius of R=0.1m (Figure 5, right). The inlet is East side and the two outlets are North and West. without curvature curvature radius R=0.1m Figure 5: Influence of the curvature radius on the flow at a T-junction TEST NETWORK FOR EXPERIMENTAL INVESTIGATIONS During the project test networks at project partners TZW (Dresden) and BWB (Berlin) are available. At these test networks the developed tools will be investigated and tested under practically relevant conditions. The network of partner TZW has a total length of about 300 m and is made of PVC-clear pipes with a diameter of 100 mm (Figure 6, left). First investigations at TZW have been performed applying several color tracers with different densities under 174
5 laminar and turbulent flow conditions (see Figure 6, right). The experiments were conducted in a straight pipe with velocities in a range of 0.004m/s to 0.5 m/s. The main results under laminar flow conditions are: 1) Dispersion is the main process for spreading and mixing, 2) The behavior (moving up or down) of the tracer depends particularly on the density of the injected liquid, 3) An injected liquid with a higher or lower density than the water moves at the pipe wall with a lower velocity than the water body. Under turbulent flow conditions, total mixing occurs immediately after injection, the position of the injection and the density of the injected liquid are not relevant. Further experiments will be done with a focus on crossand T-junctions. Figure 6: Test network for (left); Injection experiments with a color tracer (right) CONCLUSION The main objective of the project is the development of an online security management toolkit for water distribution networks (WDN) that is based on sensor measurements of water quality as well as water quantity. In this paper, the concept and first results have been presented. Actual work is focused on the implementation of the modules. ACKNOWLEDGMENTS The project is supported by the German Federal Ministry of Education and Research (BMBF; project: 13N12180) and by the French Agence Nationale de la Recherche (ANR; project: ANR-11-SECU-006). REFERENCES 1. Deuerlein, J.; Wolters, A; Meyer-Harries, L. and Simpson, A. R. (2010): Graph Decomposition in Risk Analysis and Sensor Placement for Water Distribution Network Security. Water Distribution Systems Analysis WDSA 2010, ASCE, Tucson, , September Shen, J. Y., Choi, C. Y., and Austin, R. G. (2008): Development of a Comprehensive Solute Mixing Model (AZRED) for Double-T, Cross, and Wye Junctions. Water Distribution Systems Analysis 2008, Deuerlein, J. (2008): Decomposition model of a general water supply network graph. ASCE Journal of Hydraulic Engineering, 134, 6, 2008, Deuerlein, J.; Simpson, A. R. (2012): A modified global gradient algorithm based on topological decomposition. 14 th Annual Symposium on Water Distribution Systems Analysis WDSA 2012, ASCE, Adelaide, Australia, September, Fabrie, P.; Gancel, G.; Mortazavi, I. and Piller, O. (2010): Quality Modeling of Water Distribution Systems using Sensitivity Equations. Journal of Hydraulic Engineering, 136(1), 34-44, Gleik, P. H. (2006): Water and terrorism, Water Policy, 8, , Piller, O. (1995): Modeling the behavior of a network - Hydraulic analysis and sampling procedures for parameter estimation. Applied Mathematics thesis from the University of Bordeaux (PRES), 288 pages, Talence, France, defended on the 3 rd February Piller, O., Gilbert, D. and Van Zyl, J. E. (2010): Dual Calibration for Coupled Flow and Transport Models of Water Distribution Systems. Water Distribution Systems Analysis WDSA 2010, ASCE, Tucson, , December
6 9. Propato, M. and Piller, O. (2006): Battle of the Water Sensor Networks. 8 th annual Water Distribution System Analysis Symposium, University of Cincinnati, Cincinnati, Ohio USA, August , printed by ASCE, 8, Propato, M.; Tryby, M. E. and Piller, O. (2007): Linear algebra analysis for contaminant source identification in water distribution systems. World Environmental and Water Resources Congress 2007, Tampa, Florida, USA, May 2007, 10, Preis A. and A. Ostfeld (2011): Hydraulic uncertainty inclusion in water distribution systems contamination source identification. Urban Water Journal, 8(5), ,
SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks
SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks Olivier PILLER 1, Denis GILBERT 1, Fereshte SEDEHIZADE 2, Marie MAUREL 3, Anne-Claire SANDRAZ 4, Jean-
More informationSMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks
SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks Olivier PILLER 1, Denis GILBERT 1, Fereshte SEDEHIZADE 2, Cyrille LEMOINE 3, Anne-Claire SANDRAZ 4,
More informationReal-time Monitoring Platform to Improve the Drinking Water Network Efficiency
Real-time Monitoring Platform to Improve the Drinking Water Network Efficiency SUMMARY Recent advances in real-time water sensing technology have enabled new opportunities for improved assessment and management
More informationComparison of Heat Transfer between a Helical and Straight Tube Heat Exchanger
International Journal of Engineering Research and Technology. ISSN 0974-3154 Volume 6, Number 1 (2013), pp. 33-40 International Research Publication House http://www.irphouse.com Comparison of Heat Transfer
More informationME6130 An introduction to CFD 1-1
ME6130 An introduction to CFD 1-1 What is CFD? Computational fluid dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically
More informationNUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES
Vol. XX 2012 No. 4 28 34 J. ŠIMIČEK O. HUBOVÁ NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES Jozef ŠIMIČEK email: jozef.simicek@stuba.sk Research field: Statics and Dynamics Fluids mechanics
More informationDynamic Process Modeling. Process Dynamics and Control
Dynamic Process Modeling Process Dynamics and Control 1 Description of process dynamics Classes of models What do we need for control? Modeling for control Mechanical Systems Modeling Electrical circuits
More informationDifferential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation
Differential Relations for Fluid Flow In this approach, we apply our four basic conservation laws to an infinitesimally small control volume. The differential approach provides point by point details of
More informationLecturer, Department of Engineering, ar45@le.ac.uk, Lecturer, Department of Mathematics, sjg50@le.ac.uk
39 th AIAA Fluid Dynamics Conference, San Antonio, Texas. A selective review of CFD transition models D. Di Pasquale, A. Rona *, S. J. Garrett Marie Curie EST Fellow, Engineering, ddp2@le.ac.uk * Lecturer,
More informationCFD Based Air Flow and Contamination Modeling of Subway Stations
CFD Based Air Flow and Contamination Modeling of Subway Stations Greg Byrne Center for Nonlinear Science, Georgia Institute of Technology Fernando Camelli Center for Computational Fluid Dynamics, George
More information4.What is the appropriate dimensionless parameter to use in comparing flow types? YOUR ANSWER: The Reynolds Number, Re.
CHAPTER 08 1. What is most likely to be the main driving force in pipe flow? A. Gravity B. A pressure gradient C. Vacuum 2.What is a general description of the flow rate in laminar flow? A. Small B. Large
More informationCFD Grows Up! Martin W. Liddament Ventilation, Energy and Environmental Technology (VEETECH Ltd) What is Computational Fluid Dynamics?
CIBSE/ASHRAE Meeting CFD Grows Up! Martin W. Liddament Ventilation, Energy and Environmental Technology (VEETECH Ltd) 10 th December 2003 What is Computational Fluid Dynamics? CFD is a numerical means
More informationINTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET)
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) Proceedings of the 2 nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 ISSN 0976 6340 (Print)
More informationExperiment 3 Pipe Friction
EML 316L Experiment 3 Pipe Friction Laboratory Manual Mechanical and Materials Engineering Department College of Engineering FLORIDA INTERNATIONAL UNIVERSITY Nomenclature Symbol Description Unit A cross-sectional
More informationDimensional analysis is a method for reducing the number and complexity of experimental variables that affect a given physical phenomena.
Dimensional Analysis and Similarity Dimensional analysis is very useful for planning, presentation, and interpretation of experimental data. As discussed previously, most practical fluid mechanics problems
More informationO.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt, 27.06.2012
O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM Darmstadt, 27.06.2012 Michael Ehlen IB Fischer CFD+engineering GmbH Lipowskystr. 12 81373 München Tel. 089/74118743 Fax 089/74118749
More informationExpress Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology
Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology Dimitrios Sofialidis Technical Manager, SimTec Ltd. Mechanical Engineer, PhD PRACE Autumn School 2013 - Industry
More informationOPTIMISE TANK DESIGN USING CFD. Lisa Brown. Parsons Brinckerhoff
OPTIMISE TANK DESIGN USING CFD Paper Presented by: Lisa Brown Authors: Lisa Brown, General Manager, Franz Jacobsen, Senior Water Engineer, Parsons Brinckerhoff 72 nd Annual Water Industry Engineers and
More informationPart IV. Conclusions
Part IV Conclusions 189 Chapter 9 Conclusions and Future Work CFD studies of premixed laminar and turbulent combustion dynamics have been conducted. These studies were aimed at explaining physical phenomena
More informationMATLAB AS A PROTOTYPING TOOL FOR HYDRONIC NETWORKS BALANCING
MATLAB AS A PROTOTYPING TOOL FOR HYDRONIC NETWORKS BALANCING J. Pekař, P. Trnka, V. Havlena* Abstract The objective of this note is to describe the prototyping stage of development of a system that is
More informationHydraulic Pipeline Application Modules PSI s Tools to Support Pipeline Operation
Hydraulic Pipeline Application Modules PSI s Tools to Support Pipeline Operation Inhalt 1 Leak Detection and Location Modules... 3 1.1 Dynamic Balance Leak Detection... 3 1.2 Transient Model Leak Detection...
More informationDEVELOPMENT OF HIGH SPEED RESPONSE LAMINAR FLOW METER FOR AIR CONDITIONING
DEVELOPMENT OF HIGH SPEED RESPONSE LAMINAR FLOW METER FOR AIR CONDITIONING Toshiharu Kagawa 1, Yukako Saisu 2, Riki Nishimura 3 and Chongho Youn 4 ABSTRACT In this paper, we developed a new laminar flow
More informationThe Piping System Model a New Life Cycle Document. Elements of the Piping System Model
Piping System Model as a Life Cycle Document White Paper Introduction When designing piping systems, a variety of documents are created providing the details necessary to design, purchase, build, and test
More informationSupporting document to NORSOK Standard C-004, Edition 2, May 2013, Section 5.4 Hot air flow
1 of 9 Supporting document to NORSOK Standard C-004, Edition 2, May 2013, Section 5.4 Hot air flow A method utilizing Computational Fluid Dynamics (CFD) codes for determination of acceptable risk level
More informationLeak detection in virtual DMA combining machine learning network monitoring and model based analysis
Leak detection in virtual DMA combining machine learning network monitoring and model based analysis Author Dr. Gangl Gerald*, Raúl Navas ** * Dr. Gerald Gangl, Kriegsbergstraße 31, 70327 Stuttgart, Germany,
More informationSAFEWATER Innovative tools for the detection and mitigation of CBRN related contamination events of drinking water
SAFEWATER Innovative tools for the detection and mitigation of CBRN related contamination events of drinking water 1 st CBRN Conference Antibes - Juan-les-Pins, France The need Awareness to water security
More informationNUMERICAL SIMULATION OF FLOW FIELDS IN CASE OF FIRE AND FORCED VENTILATION IN A CLOSED CAR PARK
FACULTY OF ENGINEERING NUMERICAL SIMULATION OF FLOW FIELDS IN CASE OF FIRE AND FORCED VENTILATION IN A CLOSED CAR PARK Xavier Deckers, Mehdi Jangi, Siri Haga and Bart Merci Department of Flow, Heat and
More informationCFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER
International Journal of Advancements in Research & Technology, Volume 1, Issue2, July-2012 1 CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER ABSTRACT (1) Mr. Mainak Bhaumik M.E. (Thermal Engg.)
More informationNUMERICAL INVESTIGATIONS ON HEAT TRANSFER IN FALLING FILMS AROUND TURBULENCE WIRES
NUMERICAL INVESTIGATIONS ON HEAT TRANSFER IN FALLING FILMS AROUND TURBULENCE WIRES Abstract H. Raach and S. Somasundaram Thermal Process Engineering, University of Paderborn, Paderborn, Germany Turbulence
More informationFLUID FLOW STREAMLINE LAMINAR FLOW TURBULENT FLOW REYNOLDS NUMBER
VISUAL PHYSICS School of Physics University of Sydney Australia FLUID FLOW STREAMLINE LAMINAR FLOW TURBULENT FLOW REYNOLDS NUMBER? What type of fluid flow is observed? The above pictures show how the effect
More informationA Study on Analysis of Clearwell in Water works by Computational Fluid Dynamics
, pp.217-222 http://dx.doi.org/10.14257/astl.2015. A Study on Analysis of Clearwell in Water works by Computational Fluid Dynamics Jinhong Jung 1,1, Gyewoon Choi 2, 1 Environmental and Plant Engineering
More informationCOMPUTATIONAL FLOW MODEL OF WESTFALL'S 4000 OPEN CHANNEL MIXER 411527-1R1. By Kimbal A. Hall, PE. Submitted to: WESTFALL MANUFACTURING COMPANY
COMPUTATIONAL FLOW MODEL OF WESTFALL'S 4000 OPEN CHANNEL MIXER 411527-1R1 By Kimbal A. Hall, PE Submitted to: WESTFALL MANUFACTURING COMPANY FEBRUARY 2012 ALDEN RESEARCH LABORATORY, INC. 30 Shrewsbury
More information亞 太 風 險 管 理 與 安 全 研 討 會
2005 亞 太 風 險 管 理 與 安 全 研 討 會 Asia-Pacific Conference on Risk Management and Safety Zonal Network Platform (ZNP): Applications of a state-of-the-art deterministic CFD based scientific computing tool for
More informationA Comparison of Analytical and Finite Element Solutions for Laminar Flow Conditions Near Gaussian Constrictions
A Comparison of Analytical and Finite Element Solutions for Laminar Flow Conditions Near Gaussian Constrictions by Laura Noelle Race An Engineering Project Submitted to the Graduate Faculty of Rensselaer
More informationEvent Detection in Crisis Management Systems
Event Detection in Crisis Management Systems Mats Eriksson, Fredrik Winquist, Robert Bjorklund, David Lindgren, Hans Sundgren and Ingemar Lundström Linköping University Post Print N.B.: When citing this
More informationResidual Chlorine Decay Simulation in Water Distribution System
The 7 th International Symposium on Water Supply Technology, Yokohama 2006, November 22-24, 2008, Yokohama, Japan Residual Chlorine Decay Simulation in Water Distribution System Toru Nagatani (Osaka Municipal
More informationAeroacoustic Analogy for the Computation of Aeroacoustic Fields in Partially Closed Domains
INSTITUT FÜR MECHANIK UND MECHATRONIK Messtechnik und Aktorik Aeroacoustic Analogy for the Computation of Aeroacoustic Fields in Partially Closed Domains A. Hüppe 1, M. Kaltenbacher 1, A. Reppenhagen 2,
More information3. Prescribe boundary conditions at all boundary Zones:
CFD ANALYSIS OF CHANGE IN SHAPE OF SUCTION MANIFOLD TO IMPROVE PERFORMANCE OF THE CENTRIFUGAL PUMP ABSTRACT Mr. Suraj K. Patil PG Student, Department of Mechanical Engineering /BIGCE, Solapur University,
More informationHeat Transfer Prof. Dr. Ale Kumar Ghosal Department of Chemical Engineering Indian Institute of Technology, Guwahati
Heat Transfer Prof. Dr. Ale Kumar Ghosal Department of Chemical Engineering Indian Institute of Technology, Guwahati Module No. # 04 Convective Heat Transfer Lecture No. # 03 Heat Transfer Correlation
More informationFLUID MECHANICS IM0235 DIFFERENTIAL EQUATIONS - CB0235 2014_1
COURSE CODE INTENSITY PRE-REQUISITE CO-REQUISITE CREDITS ACTUALIZATION DATE FLUID MECHANICS IM0235 3 LECTURE HOURS PER WEEK 48 HOURS CLASSROOM ON 16 WEEKS, 32 HOURS LABORATORY, 112 HOURS OF INDEPENDENT
More informationGT2011 46090 ANALYSIS OF A MICROGASTURBINE FED BY NATURAL GAS AND SYNTHESIS GAS: MGT TEST BENCH AND COMBUSTOR CFD ANALYSIS
ASME Turbo Expo 2011 June 6 10, 2011 Vancouver, Canada GT 2011 46090 ANALYSIS OF A MICROGASTURBINE FED BY NATURAL GAS AND SYNTHESIS GAS: MGT TEST BENCH AND COMBUSTOR CFD ANALYSIS M. Cadorin 1,M. Pinelli
More informationDynamic Modeling Of An Ozone Disinfection Facility
Dynamic Modeling Of An Ozone Disinfection Facility Michael Etheridge Black & Veatch 8400 Ward Parkway Kansas City, MO 64114 Presented to the Fourteenth Ozone World Congress August 25 th, 1999 ABSTRACT
More informationCFD Application on Food Industry; Energy Saving on the Bread Oven
Middle-East Journal of Scientific Research 13 (8): 1095-1100, 2013 ISSN 1990-9233 IDOSI Publications, 2013 DOI: 10.5829/idosi.mejsr.2013.13.8.548 CFD Application on Food Industry; Energy Saving on the
More informationHybrid Modeling and Control of a Power Plant using State Flow Technique with Application
Hybrid Modeling and Control of a Power Plant using State Flow Technique with Application Marwa M. Abdulmoneim 1, Magdy A. S. Aboelela 2, Hassen T. Dorrah 3 1 Master Degree Student, Cairo University, Faculty
More information. Address the following issues in your solution:
CM 3110 COMSOL INSTRUCTIONS Faith Morrison and Maria Tafur Department of Chemical Engineering Michigan Technological University, Houghton, MI USA 22 November 2012 Zhichao Wang edits 21 November 2013 revised
More informationNumerical Simulation of Thermal Stratification in Cold Legs by Using OpenFOAM
Progress in NUCLEAR SCIENCE and TECHNOLOGY, Vol. 2, pp.107-113 (2011) ARTICLE Numerical Simulation of Thermal Stratification in Cold Legs by Using OpenFOAM Jiejin CAI *, and Tadashi WATANABE Japan Atomic
More informationPerspective on R&D Needs for Gas Turbine Power Generation
Perspective on R&D Needs for Gas Turbine Power Generation Eli Razinsky Solar Turbine Incorporated 2010 UTSR Workshop October 26, 2011 1 Research Requirements Overview Specific Requirements 2 Society Requirements
More informationInternational Journal of Latest Research in Science and Technology Volume 4, Issue 2: Page No.161-166, March-April 2015
International Journal of Latest Research in Science and Technology Volume 4, Issue 2: Page No.161-166, March-April 2015 http://www.mnkjournals.com/ijlrst.htm ISSN (Online):2278-5299 EXPERIMENTAL STUDY
More informationHEAVY OIL FLOW MEASUREMENT CHALLENGES
HEAVY OIL FLOW MEASUREMENT CHALLENGES 1 INTRODUCTION The vast majority of the world s remaining oil reserves are categorised as heavy / unconventional oils (high viscosity). Due to diminishing conventional
More informationIntroduction to CFD Analysis
Introduction to CFD Analysis 2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically
More informationHEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi
HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi 2 Rajesh Dudi 1 Scholar and 2 Assistant Professor,Department of Mechanical Engineering, OITM, Hisar (Haryana)
More informationApplication of CFD modelling to the Design of Modern Data Centres
Application of CFD modelling to the Design of Modern Data Centres White Paper March 2012 By Sam Wicks BEng CFD Applications Engineer Sudlows March 14, 2012 Application of CFD modelling to the Design of
More informationINNOVATION AND COST EFFECTIVE APPROACH TO POTABLE WATER PIPE REPLACEMENT STRATEGICALLY FOCUSED ON DISTRIBUTION SYSTEM WATER QUALITY IMPROVEMENT By
INNOVATION AND COST EFFECTIVE APPROACH TO POTABLE WATER PIPE REPLACEMENT STRATEGICALLY FOCUSED ON DISTRIBUTION SYSTEM WATER QUALITY IMPROVEMENT By ABSTRACT Migdalia Hernandez, City of Sanford P.O. Box
More informationPushing the limits. Turbine simulation for next-generation turbochargers
Pushing the limits Turbine simulation for next-generation turbochargers KWOK-KAI SO, BENT PHILLIPSEN, MAGNUS FISCHER Computational fluid dynamics (CFD) has matured and is now an indispensable tool for
More informationPrediction Is Better Than Cure CFD Simulation For Data Center Operation.
Prediction Is Better Than Cure CFD Simulation For Data Center Operation. This paper was written to support/reflect a seminar presented at ASHRAE Winter meeting 2014, January 21 st, by, Future Facilities.
More informationModelling and Computation of Compressible Liquid Flows with Phase Transition
JASS 2009 - Joint Advanced Student School, Saint Petersburg, 29. 03. - 07. 04. 2009 Modelling and Simulation in Multidisciplinary Engineering Modelling and Computation of Compressible Liquid Flows with
More informationHead Loss in Pipe Flow ME 123: Mechanical Engineering Laboratory II: Fluids
Head Loss in Pipe Flow ME 123: Mechanical Engineering Laboratory II: Fluids Dr. J. M. Meyers Dr. D. G. Fletcher Dr. Y. Dubief 1. Introduction Last lab you investigated flow loss in a pipe due to the roughness
More informationGraduate Courses in Petroleum Engineering
Graduate Courses in Petroleum Engineering PEEG 510 ADVANCED WELL TEST ANALYSIS This course will review the fundamentals of fluid flow through porous media and then cover flow and build up test analysis
More informationComputational Modeling of Wind Turbines in OpenFOAM
Computational Modeling of Wind Turbines in OpenFOAM Hamid Rahimi hamid.rahimi@uni-oldenburg.de ForWind - Center for Wind Energy Research Institute of Physics, University of Oldenburg, Germany Outline Computational
More informationModel Order Reduction for Linear Convective Thermal Flow
Model Order Reduction for Linear Convective Thermal Flow Christian Moosmann, Evgenii B. Rudnyi, Andreas Greiner, Jan G. Korvink IMTEK, April 24 Abstract Simulation of the heat exchange between a solid
More informationWATER LEAKAGE AND DETECTION IN MUNICIPAL WATER DISTRIBUTION NETWORKS. N. Merzi (1) and T. Özkan (2)
Water Supply and Drainage for Buildings, 29th Int. Symposium, Turkey WATER LEAKAGE AND DETECTION IN MUNICIPAL WATER DISTRIBUTION NETWORKS N. Merzi (1) and T. Özkan (2) (1)merzi@metu.edu.tr (2)tozkan@metu.edu.tr
More informationComputational Fluid Dynamics (CFD) and Multiphase Flow Modelling. Associate Professor Britt M. Halvorsen (Dr. Ing) Amaranath S.
Computational Fluid Dynamics (CFD) and Multiphase Flow Modelling Associate Professor Britt M. Halvorsen (Dr. Ing) Amaranath S. Kumara (PhD Student), PO. Box 203, N-3901, N Porsgrunn, Norway What is CFD?
More informationTurbulence Modeling in CFD Simulation of Intake Manifold for a 4 Cylinder Engine
HEFAT2012 9 th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics 16 18 July 2012 Malta Turbulence Modeling in CFD Simulation of Intake Manifold for a 4 Cylinder Engine Dr MK
More informationEmerging Sensing Technologies for Future Intelligent Water Management Systems
Emerging Sensing Technologies for Future Intelligent Water Management Systems Johan Groen Chief Technology Officer Confluence Water Conference May 20 th, 2013 Water and Xylem Span the Entire Cycle of Water
More informationPerformance prediction of a centrifugal pump working in direct and reverse mode using Computational Fluid Dynamics
European Association for the Development of Renewable Energies, Environment and Power Quality (EA4EPQ) International Conference on Renewable Energies and Power Quality (ICREPQ 10) Granada (Spain), 23rd
More informationCustomer Training Material. Lecture 2. Introduction to. Methodology ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved.
Lecture 2 Introduction to CFD Methodology Introduction to ANSYS FLUENT L2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions,
More informationCSO Modelling Considering Moving Storms and Tipping Bucket Gauge Failures M. Hochedlinger 1 *, W. Sprung 2,3, H. Kainz 3 and K.
CSO Modelling Considering Moving Storms and Tipping Bucket Gauge Failures M. Hochedlinger 1 *, W. Sprung,, H. Kainz and K. König 1 Linz AG Wastewater, Wiener Straße 151, A-41 Linz, Austria Municipality
More informationCFD Modeling as a Tool for Clarifier Design
WEF Webcast: Optimizing Clarifier Design and Performance CFD Modeling as a Tool for Clarifier Design Outline of Presentation What is CFD? Typical Applications Activated Sludge Example Projects Benefits
More informationSimulation and capacity calculation in real German and European interconnected gas transport systems
Chapter 1 Introduction Natural gas is one of the most widely used sources of energy in Europe. The whole supply chain of natural gas, from the gas well through several kinds of elements to final customers,
More informationWATER MEASUREMENT USING TWO INCH (50 mm) DRAIN TESTS
GAP.14.1.2.2 A Publication of Global Asset Protection Services LLC WATER MEASUREMENT USING TWO INCH (50 mm) DRAIN TESTS INTRODUCTION A hydrant or other large-volume flow test is necessary for proper water
More informationA moving piston boundary condition including gap flow in OpenFOAM
A piston boundary condition including gap flow in OpenFOAM CLEMENS FRIES Johannes Kepler University IMH Altenbergerstrasse 69, 44 Linz AUSTRIA clemens.fries@jku.at BERNHARD MANHARTSGRUBER Johannes Kepler
More informationTurbulent Flow Through a Shell-and-Tube Heat Exchanger
Turbulent Flow Through a Shell-and-Tube Heat Exchanger Introduction This model describes a part of a shell-and-tube heat exchanger (see Figure 1), where hot water enters from above. The cooling medium,
More informationBasic Principles in Microfluidics
Basic Principles in Microfluidics 1 Newton s Second Law for Fluidics Newton s 2 nd Law (F= ma) : Time rate of change of momentum of a system equal to net force acting on system!f = dp dt Sum of forces
More informationQualification of Thermal hydraulic codes within NURESIM D. Bestion (CEA, France)
Qualification of Thermal hydraulic codes within NURESIM D. Bestion (CEA, France) The thermalhydraulic codes used for nuclear safety applications Validation and Verification of codes Validation of system
More informationModel of a flow in intersecting microchannels. Denis Semyonov
Model of a flow in intersecting microchannels Denis Semyonov LUT 2012 Content Objectives Motivation Model implementation Simulation Results Conclusion Objectives A flow and a reaction model is required
More information(1) 2 TEST SETUP. Table 1 Summary of models used for calculating roughness parameters Model Published z 0 / H d/h
Estimation of Surface Roughness using CFD Simulation Daniel Abdi a, Girma T. Bitsuamlak b a Research Assistant, Department of Civil and Environmental Engineering, FIU, Miami, FL, USA, dabdi001@fiu.edu
More informationLecture 6 - Boundary Conditions. Applied Computational Fluid Dynamics
Lecture 6 - Boundary Conditions Applied Computational Fluid Dynamics Instructor: André Bakker http://www.bakker.org André Bakker (2002-2006) Fluent Inc. (2002) 1 Outline Overview. Inlet and outlet boundaries.
More informationIntroduction to COMSOL. The Navier-Stokes Equations
Flow Between Parallel Plates Modified from the COMSOL ChE Library module rev 10/13/08 Modified by Robert P. Hesketh, Chemical Engineering, Rowan University Fall 2008 Introduction to COMSOL The following
More informationCFD SIMULATIONS OF WAKE EFFECTS AT THE ALPHA VENTUS OFFSHORE WIND FARM
CFD SIMULATIONS OF WAKE EFFECTS AT THE ALPHA VENTUS OFFSHORE WIND FARM Annette Westerhellweg, Thomas Neumann DEWI GmbH, Ebertstr. 96, 26382 Wilhelmshaven, Germany Phone: +49 (0)4421 4808-828 Fax: +49 (0)4421
More informationBasic Equations, Boundary Conditions and Dimensionless Parameters
Chapter 2 Basic Equations, Boundary Conditions and Dimensionless Parameters In the foregoing chapter, many basic concepts related to the present investigation and the associated literature survey were
More information2013 Code_Saturne User Group Meeting. EDF R&D Chatou, France. 9 th April 2013
2013 Code_Saturne User Group Meeting EDF R&D Chatou, France 9 th April 2013 Thermal Comfort in Train Passenger Cars Contact For further information please contact: Brian ANGEL Director RENUDA France brian.angel@renuda.com
More informationPREDICTIVE AND OPERATIONAL ANALYTICS, WHAT IS IT REALLY ALL ABOUT?
PREDICTIVE AND OPERATIONAL ANALYTICS, WHAT IS IT REALLY ALL ABOUT? Derek Vogelsang 1, Alana Duncker 1, Steve McMichael 2 1. MWH Global, Adelaide, SA 2. South Australia Water Corporation, Adelaide, SA ABSTRACT
More informationPressure drop in pipes...
Pressure drop in pipes... PRESSURE DROP CALCULATIONS Pressure drop or head loss, occurs in all piping systems because of elevation changes, turbulence caused by abrupt changes in direction, and friction
More informationRESEARCH PROJECTS. For more information about our research projects please contact us at: info@naisengineering.com
RESEARCH PROJECTS For more information about our research projects please contact us at: info@naisengineering.com Or visit our web site at: www.naisengineering.com 2 Setup of 1D Model for the Simulation
More informationWater Supply. Simulation of Water Distribution Networks. Mohammad N. Almasri. Optimal Design of Water Distribution Networks Mohammad N.
Water Supply Simulation of Water Distribution Networks The Use of EPANET Mohammad N. Almasri 1 Introduction This presentation focuses on two issues: The simulation of water distribution networks (WDNs)
More informationTWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW
TWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW Rajesh Khatri 1, 1 M.Tech Scholar, Department of Mechanical Engineering, S.A.T.I., vidisha
More informationLaminar and Turbulent flow. Flow Sensors. Reynolds Number. Thermal flow Sensor. Flow and Flow rate. R = Mass Flow controllers
Flow and Flow rate. Laminar and Turbulent flow Laminar flow: smooth, orderly and regular Mechanical sensors have inertia, which can integrate out small variations due to turbulence Turbulent flow: chaotic
More informationCOMBIMASS. Technical Data COMBIMASS eco-bio +
COMBIMASS Technical Data THE SYSTEM COMBIMASS The field transmitters of the COMBIMASS eco series are suitable for gas flow measurement and cover a wide range of different applications. The instruments
More informationPurdue University - School of Mechanical Engineering. Objective: Study and predict fluid dynamics of a bluff body stabilized flame configuration.
Extinction Dynamics of Bluff Body Stabilized Flames Investigator: Steven Frankel Graduate Students: Travis Fisher and John Roach Sponsor: Air Force Research Laboratory and Creare, Inc. Objective: Study
More informationIntrusion Detection via Machine Learning for SCADA System Protection
Intrusion Detection via Machine Learning for SCADA System Protection S.L.P. Yasakethu Department of Computing, University of Surrey, Guildford, GU2 7XH, UK. s.l.yasakethu@surrey.ac.uk J. Jiang Department
More informationIntroduction to CFD Analysis
Introduction to CFD Analysis Introductory FLUENT Training 2006 ANSYS, Inc. All rights reserved. 2006 ANSYS, Inc. All rights reserved. 2-2 What is CFD? Computational fluid dynamics (CFD) is the science
More informationMonitoring and control of openchannel flow in irrigation canals
Monitoring and control of openchannel flow in irrigation canals Xavier Litrico xavier.litrico@cemagref.fr Cemagref, UMR G-EAU, Montpellier Outline Presentation of Cemagref and UMR G-EAU Introduction Research
More informationFLOW CONDITIONER DESIGN FOR IMPROVING OPEN CHANNEL FLOW MEASUREMENT ACCURACY FROM A SONTEK ARGONAUT-SW
FLOW CONDITIONER DESIGN FOR IMPROVING OPEN CHANNEL FLOW MEASUREMENT ACCURACY FROM A SONTEK ARGONAUT-SW Daniel J. Howes, P.E. 1 Charles M. Burt, Ph.D., P.E. 2 Brett F. Sanders, Ph.D. 3 ABSTRACT Acoustic
More informationMultiphase Flow - Appendices
Discovery Laboratory Multiphase Flow - Appendices 1. Creating a Mesh 1.1. What is a geometry? The geometry used in a CFD simulation defines the problem domain and boundaries; it is the area (2D) or volume
More informationContents. Microfluidics - Jens Ducrée Physics: Fluid Dynamics 1
Contents 1. Introduction 2. Fluids 3. Physics of Microfluidic Systems 4. Microfabrication Technologies 5. Flow Control 6. Micropumps 7. Sensors 8. Ink-Jet Technology 9. Liquid Handling 10.Microarrays 11.Microreactors
More informationInitial Experiments of a Novel Liquid Desiccant Dehumidifier for Industrial and Comfort Air Conditioning Systems
Abstract Initial Experiments of a Novel Liquid Desiccant Dehumidifier for Industrial and Comfort Air Conditioning Systems M. Jaradat, R. Heinzen, U. Jordan, K. Vajen Kassel University (Germany), Institute
More informationHYBRID ROCKET TECHNOLOGY IN THE FRAME OF THE ITALIAN HYPROB PROGRAM
8 th European Symposium on Aerothermodynamics for space vehicles HYBRID ROCKET TECHNOLOGY IN THE FRAME OF THE ITALIAN HYPROB PROGRAM M. Di Clemente, R. Votta, G. Ranuzzi, F. Ferrigno March 4, 2015 Outline
More informationIncluding thermal effects in CFD simulations
Including thermal effects in CFD simulations Catherine Meissner, Arne Reidar Gravdahl, Birthe Steensen catherine@windsim.com, arne@windsim.com Fjordgaten 15, N-125 Tonsberg hone: +47 8 1800 Norway Fax:
More information